Update app.py

app.py

@@ -121,51 +121,64 @@ class DicomAnalyzer:
             return self.display_image
 
     def analyze_roi(self, evt: gr.SelectData):
-        try:
-            if self.current_image is None:
-                return None, "No image loaded"
-
-            x = int((evt.index[0] + self.pan_x) / self.zoom_factor)
-            y = int((evt.index[1] + self.pan_y) / self.zoom_factor)
-
-            height, width = self.current_image.shape[:2]
-            x = max(0, min(x, width-1))
-            y = max(0, min(y, height-1))
-
-            mask = np.zeros_like(self.current_image, dtype=np.uint8)
-            y_indices, x_indices = np.ogrid[:self.current_image.shape[0], :self.current_image.shape[1]]
-            radius = self.circle_diameter / 2
-            distance_from_center = np.sqrt(
-                (x_indices - x)**2 + (y_indices - y)**2
-            )
-            mask[distance_from_center <= radius] = 1
-
-            roi_pixels = self.current_image[mask == 1]
-
-            pixel_spacing = float(self.dicom_data.PixelSpacing[0])
-            area_pixels = np.sum(mask)
-            area_mm2 = area_pixels * (pixel_spacing ** 2)
-            mean = np.mean(roi_pixels)
-            stddev = np.std(roi_pixels)
-            min_val = np.min(roi_pixels)
-            max_val = np.max(roi_pixels)
-
-            result = {
-                'Area (mm²)': f"{area_mm2:.3f}",
-                'Mean': f"{mean:.3f}",
-                'StdDev': f"{stddev:.3f}",
-                'Min': f"{min_val:.3f}",
-                'Max': f"{max_val:.3f}",
-                'Point': f"({x}, {y})"
-            }
-            self.results.append(result)
-            self.marks.append((x, y, self.circle_diameter))
-            print(f"ROI analyzed at point ({x}, {y})")
+    try:
+        if self.current_image is None:
+            return None, "No image loaded"
+
+        # Get the clicked coordinates
+        clicked_x = evt.index[0]
+        clicked_y = evt.index[1]
+
+        # Adjust for pan and zoom
+        x = int((clicked_x + self.pan_x) / self.zoom_factor)
+        y = int((clicked_y + self.pan_y) / self.zoom_factor)
+
+        # Ensure coordinates are within image bounds
+        height, width = self.current_image.shape[:2]
+        x = max(0, min(x, width-1))
+        y = max(0, min(y, height-1))
+
+        # Create mask for ROI
+        mask = np.zeros_like(self.current_image, dtype=np.uint8)
+        y_indices, x_indices = np.ogrid[:self.current_image.shape[0], :self.current_image.shape[1]]
+        radius = self.circle_diameter / 2
+        distance_from_center = np.sqrt(
+            (x_indices - x)**2 + (y_indices - y)**2
+        )
+        mask[distance_from_center <= radius] = 1
+
+        # Calculate statistics
+        roi_pixels = self.current_image[mask == 1]
+        pixel_spacing = float(self.dicom_data.PixelSpacing[0])
+        area_pixels = np.sum(mask)
+        area_mm2 = area_pixels * (pixel_spacing ** 2)
+        mean = np.mean(roi_pixels)
+        stddev = np.std(roi_pixels)
+        min_val = np.min(roi_pixels)
+        max_val = np.max(roi_pixels)
+
+        # Adjust coordinates to match ImageJ coordinate system
+        # ImageJ coordinates start from top-left
+        imagej_x = x
+        imagej_y = y
+
+        result = {
+            'Area (mm²)': f"{area_mm2:.3f}",
+            'Mean': f"{mean:.3f}",
+            'StdDev': f"{stddev:.3f}",
+            'Min': f"{min_val:.3f}",
+            'Max': f"{max_val:.3f}",
+            'Point': f"({imagej_x}, {imagej_y})"
+        }
+        
+        self.results.append(result)
+        self.marks.append((x, y, self.circle_diameter))
+        print(f"ROI analyzed at point ({imagej_x}, {imagej_y})")
 
-            return self.update_display(), self.format_results()
-        except Exception as e:
-            print(f"Error analyzing ROI: {str(e)}")
-            return self.display_image, f"Error analyzing ROI: {str(e)}"
+        return self.update_display(), self.format_results()
+    except Exception as e:
+        print(f"Error analyzing ROI: {str(e)}")
+        return self.display_image, f"Error analyzing ROI: {str(e)}"
 
     def update_display(self):
         try: